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» New Regularized Algorithms for Transductive Learning
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ICML
2010
IEEE
15 years 21 days ago
A scalable trust-region algorithm with application to mixed-norm regression
We present a new algorithm for minimizing a convex loss-function subject to regularization. Our framework applies to numerous problems in machine learning and statistics; notably,...
Dongmin Kim, Suvrit Sra, Inderjit S. Dhillon
COLT
2006
Springer
15 years 3 months ago
Maximum Entropy Distribution Estimation with Generalized Regularization
Abstract. We present a unified and complete account of maximum entropy distribution estimation subject to constraints represented by convex potential functions or, alternatively, b...
Miroslav Dudík, Robert E. Schapire
ICML
2010
IEEE
15 years 21 days ago
Feature Selection Using Regularization in Approximate Linear Programs for Markov Decision Processes
Approximate dynamic programming has been used successfully in a large variety of domains, but it relies on a small set of provided approximation features to calculate solutions re...
Marek Petrik, Gavin Taylor, Ronald Parr, Shlomo Zi...
CIKM
2008
Springer
15 years 1 months ago
Active relevance feedback for difficult queries
Relevance feedback has been demonstrated to be an effective strategy for improving retrieval accuracy. The existing relevance feedback algorithms based on language models and vect...
Zuobing Xu, Ram Akella
NIPS
2008
15 years 1 months ago
Privacy-preserving logistic regression
This paper addresses the important tradeoff between privacy and learnability, when designing algorithms for learning from private databases. We focus on privacy-preserving logisti...
Kamalika Chaudhuri, Claire Monteleoni